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The Complete Natural Language Processing (NLP) Course

@machinelearnbot

Welcome to this course: The Complete Natural Language Processing (NLP) Course. Natural language processing (NLP) is a field of computer science, artificial intelligence and computational linguistics concerned with the interactions between computers and human (natural) languages, and, in particular, concerned with programming computers to fruitfully process large natural language corpora. Natural Language Processing (NLP) is used in many applications to provide capabilities that were previously not possible. It involves analyzing text to obtain intent and meaning, which can then be used to support an application. This comprehensive course will get you up-and-running with advanced tasks using Natural Language Processing Techniques with Python.


Data Science: Natural Language Processing (NLP) in Python

@machinelearnbot

In this course you will build MULTIPLE practical systems using natural language processing, or NLP - the branch of machine learning and data science that deals with text and speech. This course is not part of my deep learning series, so it doesn't contain any hard math - just straight up coding in Python. All the materials for this course are FREE. After a brief discussion about what NLP is and what it can do, we will begin building very useful stuff. The first thing we'll build is a spam detector.


Make games in Unreal and apps with Python machine learning

#artificialintelligence

Make your first mobile app and game here. Learn how to code and make games in the popular Unreal Engine 4. Learn by building 6 actual games. Make next-level apps that use machine learning with Java, Android, TensorFlow Estimator, PyCharm, and MNIST. By taking this course you will make 3 complete mobile machine learning models and apps. We will build a simple weather prediction project, stock market prediction project, and text-response project.


Reinforcement Learning from scratch โ€“ Insight Data

#artificialintelligence

Recently, I gave a talk at the O'Reilly AI conference in Beijing about some of the interesting lessons we've learned in the world of NLP. While there, I was lucky enough to attend a tutorial on Deep Reinforcement Learning (Deep RL) from scratch by Unity Technologies. I thought that the session, led by Arthur Juliani, was extremely informative and wanted to share some big takeaways below. In our conversations with companies, we've seen a rise of interesting Deep RL applications, tools and results. In parallel, the inner workings and applications of Deep RL, such as AlphaGo pictured above, can often seem esoteric and hard to understand.


Data-driven Astronomy Coursera

@machinelearnbot

Science is undergoing a data explosion, and astronomy is leading the way. Modern telescopes produce terabytes of data per observation, and the simulations required to model our observable Universe push supercomputers to their limits. To analyse this data scientists need to be able to think computationally to solve problems. In this course you will investigate the challenges of working with large datasets: how to implement algorithms that work; how to use databases to manage your data; and how to learn from your data with machine learning tools. The focus is on practical skills - all the activities will be done in Python 3, a modern programming language used throughout astronomy.


Varieties of Mind Conference

#artificialintelligence

The study of artificial intelligence has frequently benefitted from close engagement with other branches of cognitive science, and computational theories of cognition have in turn contributed to models of the mind in philosophy, neuroscience, and animal cognition. However, even as we stand at the threshold of a new era of developments in artificial intelligence, disciplinary differences and disparate theoretical vocabularies still linger, and the goal of a unifying theory of human, animal, and artificial minds remains elusive. To that end, the Varieties of Mind conference aims to bring together leading researchers in psychology, animal cognition, artificial intelligence, and philosophy of mind to explore questions including the following. Please note that purchasing full conference tickets includes Public Lecture 1, Public Lecture 2, Debate 1 and Debate 2. There is no need to sign up to the other events. To be added to the waiting list, please contact Gaenor Moore.


Learning Path: Scala: Efficient Data Analysis with Scala

@machinelearnbot

Data analysis is a process for inspecting, consolidating, transforming, and making sense of data in a way that guides the decision-making process. Scala has emerged as an important tool for efficiently performing various data analysis tasks. So, if you're interested to load raw datasets with Spark, and perform exploratory data analysis on those via plotting Scala libraries, then go for this Learning Path. Packt's Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it. Let's take a quick look at your learning journey.


The future of AI, IoT and 5G is in the fog - IoT Agenda

#artificialintelligence

We are at a pivotal moment in technical advancements, where waves of digital innovation are changing how we work, play, travel, communicate, dine, interact and even think. The Internet of Things (IoT) world may be exciting, but there are serious technical challenges that need to be addressed, especially by developers. In this handbook, learn how to meet the security, analytics, and testing requirements for IoT applications. You forgot to provide an Email Address. This email address doesn't appear to be valid. This email address is already registered.


Medical Neuroscience Coursera

@machinelearnbot

Medical Neuroscience explores the functional organization and neurophysiology of the human central nervous system, while providing a neurobiological framework for understanding human behavior. In this course, you will discover the organization of the neural systems in the brain and spinal cord that mediate sensation, motivate bodily action, and integrate sensorimotor signals with memory, emotion and related faculties of cognition. The overall goal of this course is to provide the foundation for understanding the impairments of sensation, action and cognition that accompany injury, disease or dysfunction in the central nervous system. The course will build upon knowledge acquired through prior studies of cell and molecular biology, general physiology and human anatomy, as we focus primarily on the central nervous system. This online course is designed to include all of the core concepts in neurophysiology and clinical neuroanatomy that would be presented in most first-year neuroscience courses in schools of medicine.


IATA - AI White Paper

#artificialintelligence

The Artificial Intelligence (AI) White Paper outlines the results of IATA research and development activities on AI in collaboration with airlines and the wider value chain. You will discover in this White Paper the fundamentals, threats and opportunities of AI across the aviation industry.